Data Analyst

Oliver Tolas Healthcare Packaging•Grand Rapids, MI

5d•Onsite

About The Position

The Data Analyst is responsible for developing business intelligence and analytics tools across the organization. The position will work closely with key stakeholders from various departments and work closely with them to validate and deploy the tools to users, as well as using the tools developed to provide insight and recommendations based on the analysis conducted. The Data Analyst plays a lead role in driving the culture of data driven decision making and its adoption across the organization.

Requirements

Bachelor’s Degree in Sales, Marketing, Business or Finance preferred
3+ years’ experience working with database applications, reporting and analysis.
Equivalent Combination of Education and Experience
Strong critical thinking, analytical, and research skills.
Experience using Tableau, SAP Analytics Cloud or similar business intelligence tool.
Strong Mathematical foundation.
Expert in Microsoft Office; Excel specifically.
Deep experience in enterprise and database applications.
Report writing know-how is a plus.

Nice To Haves

Ability to write in a clear and concise manner, etc.
Ability to communicate with business users across the organization.
Ability to speak effectively, present information, respond to questions in a clear and concise manner, etc.
Must demonstrate attention to detail, be able to work independently or as member of a team.

Responsibilities

Work closely with business leaders to develop and maintain intelligence and analytics tools & KPIs.
Deploy and train business users on the tools.
Support the forecasting process by helping to drive the commercial team’s sales forecast, including tracking of New and At-Risk Business, as well as providing insight based on scenarios developed throughout the forecasting process.
Monitor data integrity and initiate processes to improve data harmony across Oliver facilities globally.
Lead information management projects to improve accuracy, access, and process efficiency.
Facilitate and Drive S&OP process.
Identify areas of risk that need increased visibility and develop process improvements.
Develop standards and procedures for the organization related to data management.
Support the business’ data needs by providing information such as material usage and sales or customer lists from CRM.
Administer Sales Team variable compensation calculation.
Perform ad-hoc intelligence and data mining requests as needed.